How does this skill improve upon standard image prompting for Nano Banana?

It gives the agent a repeatable prompt structure: subject, action, setting, composition, lighting, and exact product text. It helps diagnose text and material errors, but generated results still need review.

Which specific models and AI environments are compatible with this skill?

The SKILL.md method is written for Nano Banana image generation. It includes Magnific model and tool notes, but the prompt principles also work in other agents that can send images and text to Nano Banana. Check your provider’s current model options before running.

What assets and documentation are included in the purchase?

The ZIP contains SKILL.md, a commercial license, third-party notices, a cinematic-language reference, and a model-capabilities reference. It is a written prompting guide, not a model, API integration, or asset library.

Can I use these prompting techniques to generate consistent video sequences?

No, this skill is strictly optimized for high-fidelity still images; video generation requires a different prompt architecture not covered by this specific toolset.

How does the skill handle complex typographic requirements or non-Latin scripts?

It instructs the agent to quote the exact string, specify its style and placement, then verify the result. Arabic joining and all product text still need human review. For critical logos or labels, composite the real mark in post if generation fails.

What is the initial setup process for implementing these prompts into my workflow?

Install the SKILL.md in a compatible agent and provide a product image or brief. Magnific library @name references are optional and only apply if you use that platform; a normal image reference also works.

Nano Banana Prompting for Ad Frames

Summary

Illustrative reference-driven prompt for Nano Banana Pro at 9:16. Check current resolution support in your provider. The can's identity comes from your packshot and the label text is quoted exactly. The top-right is kept empty for type set in post.

Settings

Setting	Value	Why
Model	Nano Banana Pro	Chosen for this example after checking current reference and text capabilities; confirm availability and price in your provider
Aspect ratio	9:16	Vertical delivery
Resolution	Check live provider options	Select enough pixels for final delivery
Reference	packshot.png (role: product)	Identity comes from the image, not from a description

Prompt

Use the attached product photo as the exact can: same shape, colours and label.
A single NOMAD cold-brew can stands upright on a weathered limestone ledge in the old mud-brick district of Diriyah, late golden hour. The can sits in the left third of the frame, slightly below centre. Behind it, soft out-of-focus mud-brick walls glow warm amber.
Shot on an 85mm lens at eye level with the can, shallow depth of field: the label is tack-sharp and the background falls off into smooth bokeh. Low warm sun from the right rakes across the can, catching condensation droplets on the aluminium, with a soft natural shadow falling left.
The label reads exactly "NOMAD COLD BREW" in its original typeface, crisp and legible.
The upper-right area of the frame is open, calm sky and soft wall texture with nothing in it, leaving clear space for a headline.
Photorealistic commercial product photography, natural colour, fine detail.

Why it's written this way

Brief, not caption: subject, location, composition, lens, light and text are each stated once.
Positive framing: "the upper-right area is open, calm sky" works better than "no text, no objects top-right".

Text rule: the can's label is product text, so it is quoted and generated. The Arabic headline is ad copy, so it's kept out and set in post.

If it comes back wrong

Label garbled: re-roll once, then edit the image with only the label region changed.
The can drifts from the packshot: move the reference instruction to the first line and remove any descriptive colour words that conflict with it.

About this skill

Use this skill after you know the product reference and visual direction. It turns those decisions into a Nano Banana prompt for a product frame, keyframe, reference sheet or end card. The prompt specifies what each reference controls, how the scene is lit and framed, which real product text must stay exact, and where editable ad copy will be added later.

You receive a ready-to-send prompt and a check list for identity, packaging text, composition and reproducibility.

Model availability, resolution and credit cost come from your current generation tool, not a fixed price table. Bring your own model access.

Frequently Asked Questions

Nano Banana Prompting for Ad Frames